题名

Product Bundling in the Electronic Commerce Environment: A Hybrid Approach

DOI

10.6186/IJIMS.2015.26.4.5

作者

Wen-Yau Liang;Chun-Che Huang

关键词

E-commerce ; product bundling ; rough set theory ; genetic algorithm

期刊名称

International Journal of Information and Management Sciences

卷期/出版年月

26卷4期(2015 / 12 / 01)

页次

393 - 410

内容语文

英文

英文摘要

Product bundling is a widespread practice in the current e-commerce environment. How- ever, there are few investigations about bundled commodities mining. Because no efficient method of product bundling is currently available, an expert selection of appropriate product bundling is a complex process. This is time-consuming and cannot efficiently meet the enterprise’s need. It is essential for a company to develop product bundling based on analyzing the related information that fits different requirements and maximizes the benefit. This study proposes a method of incorporating GA and rough set theory. The superiority of the proposed GA is its ability to model problems and explore solutions generically. The proposed method improves GA performance by reducing the domain range of the initial population and constrained crossover using rough set theory. The experimental results in this study confirm that this approach is highly effective and very promising.

主题分类 基礎與應用科學 > 資訊科學
社會科學 > 管理學
参考文献
  1. Adomavicius, G.,Tuzhilin, A.(2005).Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions.IEEE Transactions on Knowledge and Data Engineering,17(6),734-749.
  2. Aflori, C.,Craus, M.(2007).Grid implementation of the Apriori algorithm.Advances in Engineering Software,38(5),295-300.
  3. Agrawal, R.,Srikant, R.(1994).Fast algorithms for mining association rules.Proc. 20th Int. Conf. Very Large Data Bases, VLDB,1215,487-499.
  4. Ahn, H.,Kim, K. J.(2009).Bankruptcy prediction modeling with hybrid case-based reasoning and genetic algorithms approach.Applied Soft Computing,9(2),599-607.
  5. Aliman, N. K.,Othman, M. N.(2007).Purchasing local and foreign brands: What product attributes metter?.Proceedings of the 13th Asia Pacific Management Conference,Melbourne, Australia:
  6. Beckwith, H.(2000).The Invisible Touch.New York:Warner Books.
  7. Beynon, M. J.,Peel, M. J.(2001).Variable precision rough set theory and data discretisation: an application to corporate failure prediction.Omega,29(6),561-576.
  8. Bobadilla, J.,Ortega, F.,Hernando, A.(2012).A collaborative filtering similarity measure based on singularities.Information Processing & Management,48(2),204-217.
  9. Bueno, R.,Traina, A. J. M.,Traina, C. T.(2007).Genetic algorithms for approximate similarity queries.Data and Knowledge Engineering,62,459-482.
  10. Chang, S. A.,Tayi, G. K.(2009).An analytical approach to bundling in the presence of customer transition effects.Decision Support Systems,48(1),122-132.
  11. Chen, T. C.,Hsu, T. C.(2006).A GAs based approach for mining breast cancer pattern.Expert Systems with Applications,30(4),674-681.
  12. Chen, Y. C.,Shang, R. A.,Kao, C. Y.(2009).The effects of information overload on consumers' subjective state towards buying decision in the internet shopping environment.Electronic Commerce Research and Applications,8(1),48-58.
  13. Cretu, A. E.,Brodie, R. J.(2007).The influence of brand image and company reputation where manufacturers market to small firms: A customer value perspective.Industrial Marketing Management,36(2),230-240.
  14. Eppen, G. D.,Hanson, W. A.,Martin, R. K.(1991).Bundling-new products, new markets, low risk.Sloan Management Review,32(4),7.
  15. Garfinkel, R.,Gopal, R.,Tripathi, A.,Yin, F.(2006).Design of a shopbot and recommender system for bundle purchases.Decision Support Systems,42,1974-1986.
  16. Ghani, U.,Salaria, M. R.,Jan, F. A.(2007).Country-of-Origin effect on consumer purchase decision of durable goods in pakistan.Journal of Management Sciences,1(1),40-51.
  17. Gosselin, L.,Tye-Gingras, M.,Mathieu-Potvin, F.(2009).Review of utilization of genetic al-gorithms in heat transfer problems.International Journal of Heat and Mass Transfer,52(9),2169-2188.
  18. Guiltinan, J. P.(1987).The price bundling of services: a normative framework.The Journal of Marketing,51(2),74-85.
  19. Han, J.,Kamber, M.(2007).Data Mining: Concepts and Techniques.Morgan Kaufmann Publishers.
  20. Harik, G.,Lobo, F.,Goldberg, D. E.(1998).The compact genetic algorithm.Proceedings of the IEEE International Conference on Evolutionary Computation
  21. Holland, J. H.(1975).Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence.U Michigan Press.
  22. Hu, Y. C.,Hu, J. S.,Chen, R. S.,Tzeng, G. H.(2004).Assessing weights of product attributes from fuzzy knowledge in a dynamic environment.European Journal of Operational Research,154(1),125-143.
  23. Huang, C. C.,Tseng, T. L. B.(2004).Rough set approach to case-based reasoning application.Expert Systems with Applications,26(3),369-385.
  24. Kadri, B.,Boussahla, M.,Bendimerad, F. T.(2010).Phase-only planar antenna array synthesis with fuzzy genetic algorithms.International Journal of Computer Science,7(2),72-77.
  25. Kim, T. U.,Shin, J. W.,Hwang, I. H.(2007).Stacking sequence design of a composite wing under a random gust using a genetic algorithm.Computers & structures,85(10),579-585.
  26. Koivumki, T.,Svento, R.,Perttunen, J.,Oinas-Kukkonen, H.(2002).Consumer choice behavior and electronic shopping systems-a theoretical note.Netnomics,4(2),131-144.
  27. Kotler, P.(1996).Marketing management: Analysis, Planning, Implementation, and Control.New Jersey:Prentice Hall.
  28. Leung, Y.,Fischer, M. M.,Wu, W. Z.,Mi, J. S.(2008).A rough set approach for the discovery of classification rules in interval-valued information systems.International Journal of Approximate Reasoning,47(2),233-246.
  29. Liang, W. Y.,Huang, C. C.(2008).A hybrid approach to constrained evolutionary computing: Case of product synthesis.Omega,36,1072-1085.
  30. Liao, S. H.,Chen, J. L.,Hsu, T. Y.(2009).Ontology-based data mining approach implemented for sport marketing.Expert Systems with Applications,36,11045-11056.
  31. Liu, X.,Zeng, X.,Xu, Y.,Koehl, L.(2008).A fuzzy model of customer satisfaction index in e-commerce.Mathematics and Computers in Simulation,77,512-521.
  32. Loudon, D.,Della Bitta, A. J.(1993).Consumer Behavior: Concepts and Applications.New York:McGraw Hill.
  33. Ma, Y.,Zhang, C.(2008).Quick convergence of genetic algorithm for QoS-driven web service selection.Computer Networks,52,1093-1104.
  34. Magro, M. C.,Pinceti, P.(2009).A confirmation technique for predictive maintenance using the Rough Set Theory.Computers and Industrial Engineering,56(4),1319-1327.
  35. Mahdavi, I.,Paydar, M. M.,Solimanpur, M.,Heidarzade, A.(2009).Genetic algorithm approach for solving a cell formation problem in cellular manufacturing.Expert Systems with Applications,36,6598-6604.
  36. McCardle, K. F.,Rajaram, K.,Tang, C. S.(2007).Bundling retail products: Models and analysis.European Journal of Operational Research,177,1197-1217.
  37. Nah, F. F. H.(2004).A study on tolerable waiting time: How long are web users willing to wait.Behavior and Information Technology,23(3),153-163.
  38. Oklobdzija, V. G.(2002).The Computer Engineering Handbook.CRC Press.
  39. Ovans, A.(1997).Make a bundle bundling.Harvard Business Review,75(6),18-20.
  40. Park, D. H.,Lee, J.(2008).eWOM overload and its effect on consumer behavioral intention depending on consumer involvement.Electronic Commerce Research and Applications,7,386-398.
  41. Pattaraintakorn, P.,Cercone, N.,Naruedomkul, K.(2006).Rule learning: Ordinal prediction based on rough sets and soft-computing.Applied Mathematics Letters,19(12),1300-1307.
  42. Pawlak, Z.(1991).Rough sets: theoretical aspects of reasoning about data.Norwell, MA:Kluwer Academic Publishers.
  43. Pu, P.,Chen, L.,Hu, R.(2012).Evaluating recommender systems from the user's perspective: survey of the state of the art.User Modeling and User-Adapted Interaction,22,317-355.
  44. Questier, F.,Arnaut-Rollier, I.,Walczak, B.,Massart, D. L.(2002).Application of rough set theory to feature selection for unsupervised clustering.Chemometrics and Intelligent Laboratory Systems,63(2),155-67.
  45. Shih, H. Y.(2008).Contagion effects of electronic commerce diffusion: Perspective from network analysis of industrial structure.Technological Forecasting and Social Change,75,78-90.
  46. Shyng, J. Y.,Wang F. K.,Tzeng, G. H.,Wu, K. S.(2007).Rough Set Theory in analyzing the attributes of combination values for the insurance market.Expert Systems with Applications,32(1),56-64.
  47. Song, M.,Song, I. Y.,Hu, X.,Allen, R. B.(2007).Integration of association rules and ontologies for semantic query expansion.Data and Knowledge Engineering,63,63-75.
  48. Tseng, T. L.,Huang, C. C.(2007).Rough set-based approach to feature selection in customer relationship management.Omega,35,365-383.
  49. Vlaev, I.,Chater, N.,Lewis, R.,Davies, G.(2009).Reason-based judgments: Using reasons to decouple perceived price-quality correlation.Journal of Economic Psychology,30,721-731.
  50. Xia, W.,Wu, Z.(2007).Supplier selection with multiple criteria in volume discount environments.Omega,35(5),494-504.
  51. Xiao, B.,Benbasat, I.(2007).Ecommerce product recommendation agents: use, characteristics, and impact.MIS Q.,31,137-209.
  52. Yang, H. H.,Liu, T. C.,Lin, Y.T.(2007).Applying rough sets to prevent customer complaints for IC packaging foundry.Expert Systems with Applications,32(1),151-156.
  53. Yang, H. H.,Wu, C. L.(2009).Rough sets to help medical diagnosis-Evidence from a Taiwan's clinic.Expert Systems with Applications,36,9293-9298.
  54. Yin, Y.(2008).An approach to mining bundled commodities.Knowledge-Based Systems,21,321-331.
  55. Yu, P. L.(1980).Behavior bases and habitual domains of human decision/behavior-concepts and applications.Multiple Criteria Decision Making Theory and Application,177,511-539.
  56. Zhao, Y.,Yao,Y.,Luo, F.(2007).Data analysis based on discernibility and indiscernibility.Information Sciences,177(22),4959-4976.
  57. Ziarko, W. P.,Rijsbergen, C. J.(1994).Rough Sets, Fuzzy Sets and Knowledge Discovery.New York:Springer.